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In order to predict monthly rainfall total over Indramayu district SST data of GeM outputs can be used as a predictor. The advantage of GeM outputs is that data could be derived spatially and temporally. Unfortunately, the used of GeM outputs directly to provide total rainfall prediction for local and regional scales are considered improper because these outputs can not provide some features of local and regional scales. This condition is the disadvantage of global model outputs. In this case, it is necessary to apply Statistical Downscaling (SD) technique. This paper discusses the use of Partial Least Square Regression (PLSR) as SD technique using 49 grid points SST of 10 x 10 resolution of GeM to predict monthly rainfall total in Indramayu district. The results show that Pearson correlation coefficient range is 0,48 to 0,88 and the RMSE range is 43 mm per month to 133 mm per month. Anjatan station shows the best performance.